Existing forecasting and scheduling solutions allow call center managers to forecast workload and schedule the right number of skilled agents at the right times to meet their service goals. However, existing solutions do not factor quality of performance in determining a schedule. Therefore, call center supervisors have had to use inefficient manual processes, including manual scheduling of agents, to ensure that customers receive the desired service quality.
In addition, call centers have access to data about the quality of calls that are serviced. This data is collected based on a sophisticated set of voice recordings, forms filled out by supervisors, and other means for automatically and semi-automatically evaluating how well a call/customer was serviced. This data is kept as call details (e.g., time of day/date, type of call, customer information, etc.) and as agent details (e.g., name of agent, skills, experience, etc.). In addition, call centers can also have access to details regarding the actual schedule of agent operations (e.g., days, dates that agents worked, including their work shifts and break times, agent skills) and the actual record of call statistics overall (e.g., call service levels achieved, queue sizes, abandonment rates—all for various times of days, days of weeks, specific dates, etc.).